EP4254005A1 - Dispositif électronique, procédé de commande de dispositif électronique et programme - Google Patents

Dispositif électronique, procédé de commande de dispositif électronique et programme Download PDF

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Publication number
EP4254005A1
EP4254005A1 EP21897741.1A EP21897741A EP4254005A1 EP 4254005 A1 EP4254005 A1 EP 4254005A1 EP 21897741 A EP21897741 A EP 21897741A EP 4254005 A1 EP4254005 A1 EP 4254005A1
Authority
EP
European Patent Office
Prior art keywords
electronic device
probability density
transmission
density distribution
wave
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21897741.1A
Other languages
German (de)
English (en)
Inventor
Tooru Sahara
Jun Kuroda
Kenji Yamamoto
Takuya Homma
Fangwei Tong
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Kyocera Corp
Original Assignee
Kyocera Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Kyocera Corp filed Critical Kyocera Corp
Publication of EP4254005A1 publication Critical patent/EP4254005A1/fr
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/32—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated
    • G01S13/34—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal
    • G01S13/343—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal using sawtooth modulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/42—Simultaneous measurement of distance and other co-ordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/50—Systems of measurement based on relative movement of target
    • G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G01S13/583—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets
    • G01S13/584—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets adapted for simultaneous range and velocity measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/03—Details of HF subsystems specially adapted therefor, e.g. common to transmitter and receiver
    • G01S7/032—Constructional details for solid-state radar subsystems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/356—Receivers involving particularities of FFT processing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/415—Identification of targets based on measurements of movement associated with the target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Definitions

  • the present disclosure relates to an electronic device, a method for controlling an electronic device, and a program.
  • a technology for measuring a distance or the like between a vehicle of interest and a predetermined object is regarded as important.
  • various studies have been conducted particularly on a radar (Radio Detecting and Ranging) technology for measuring a distance or the like to an object such as an obstacle by transmitting a radio wave such as a millimeter wave and then receiving a reflected wave reflected off the object.
  • a radar Radio Detecting and Ranging
  • Such a technology for measuring a distance or the like expectedly becomes more important in the future with progresses of a technology for assisting drivers in driving and an automated-driving-related technology for partially or entirely automating driving.
  • Patent Literature 1 discloses a pedestrian detection apparatus that irradiates an observation target in front of the apparatus with an electromagnetic wave, and determines whether the observation target is a pedestrian based on a reflected wave of the electromagnetic wave.
  • Non Patent Literature 1 discusses target classification for classifying pedestrians, bicycles, and automobiles by accumulating information acquired with a radar and performing machine learning of the information.
  • Patent Literature 1 Japanese Unexamined Patent Application Publication No. 2015-190777
  • Non Patent Literature 1 Yoichi Tomiki and three others, "Examination of Target Classification for Millimeter-Wave Radar", Japan Radio Company Review (JRC REVIEW), Japan Radio Co., Ltd., 2017, No.68, ISSN 0287-1564, p. 17
  • an electronic device includes a transmission antenna, a reception antenna, and a controller.
  • the transmission antenna transmits a transmission wave.
  • the reception antenna receives a reflected wave that is the transmission wave having been reflected.
  • the controller detects an object that reflects the transmission wave, based on a transmission signal transmitted as the transmission wave and a reception signal received as the reflected wave.
  • the controller classifies a predetermined target, based on a probability density distribution calculated from a relative velocity of the object relative to the electronic device.
  • a method for controlling an electronic device includes
  • a program causes
  • the processing load of classifying a target is desirably reduced in a technology for detecting a predetermined object by receiving a reflected wave that is a transmitted transmission wave reflected off the object.
  • the present disclosure provides an electronic device, a method for controlling an electronic device, and a program that can reduce the processing load of classifying a target.
  • an electronic device, a method for controlling an electronic device, and a program that can reduce the processing load of classifying a target can be provided. The one embodiment is described in detail below with reference to the drawings.
  • An electronic device is mounted in a vehicle (mobility device) such as an automobile, for example, and is capable of detecting, as a target, a predetermined object located around the mobility device.
  • the electronic device according to the one embodiment is capable of transmitting a transmission wave to an area around the mobility device from a transmission antenna installed on or in the mobility device.
  • the electronic device according to the one embodiment is also capable of receiving a reflected wave that is the reflected transmission wave, from a reception antenna installed on or in the mobility device.
  • a radar sensor or the like installed on or in the mobility device may include at least one of the transmission antenna or the reception antenna.
  • the mobility device in which the electronic device according to the one embodiment is mounted is not limited to an automobile.
  • the electronic device according to the one embodiment may be mounted in various mobility devices such as an autonomous car, a bus, a truck, a taxi, a motorcycle, a bicycle, a ship, an aircraft, a helicopter, agricultural machinery such as a tractor, a snowplow, a garbage truck, a police car, an ambulance, and a drone.
  • the mobility device in which the electronic device according to the one embodiment is mounted is not necessarily limited to a mobility device that moves by its own motive power.
  • the mobility device in which the electronic device according to the one embodiment is mounted may be a trailer towed by a tractor.
  • the electronic device according to the one embodiment is capable of measuring a distance or the like between a sensor and a predetermined object when at least one of the sensor or the object is movable.
  • the electronic device according to the one embodiment is also capable of measuring a distance or the like between the sensor and the object even when both the sensor and the object are stationary.
  • the automobile encompassed by the present disclosure is not limited by the overall length, the overall width, the overall height, the displacement, the seating capacity, the load, or the like.
  • the automobiles of the present disclosure include an automobile having a displacement greater than 660 cc and an automobile having a displacement equal to or less than 660 cc that is a so-called light automobile.
  • the automobiles encompassed by the present disclosure also include an automobile that partially or entirely uses electricity as energy and uses a motor.
  • FIG. 1 is a diagram for describing how the electronic device according to the one embodiment is used.
  • FIG. 1 illustrates an example in which a sensor, including a transmission antenna and a reception antenna, according to the one embodiment is installed on a mobility device.
  • a mobility device 100 illustrated in FIG. 1 includes a sensor 5 installed thereon.
  • the sensor 5 according to the one embodiment includes a transmission antenna and a reception antenna.
  • the mobility device 100 illustrated in FIG. 1 includes an electronic device 1 according to the one embodiment mounted (for example, built) therein. A specific configuration of the electronic device 1 is described later.
  • the sensor 5 may include at least one of the transmission antenna or the reception antenna, for example.
  • the sensor 5 may appropriately include at least any of other functional units, such as at least part of a controller 10 ( FIG. 2 ) included in the electronic device 1.
  • the mobility device 100 illustrated in FIG. 1 may be an automotive vehicle such as a passenger car but may be a mobility device of any type. In FIG. 1 , the mobility device 100 may move (travel or slowly travel), for example, in a positive Y-axis direction (traveling direction) illustrated in FIG. 1 or in another direction, or may be stationary without moving.
  • the sensor 5 including the transmission antenna is installed on the mobility device 100.
  • only one sensor 5 including the transmission antenna and the reception antenna is installed at a front portion of the mobility device 100.
  • the position where the sensor 5 is installed on the mobility device 100 is not limited to the position illustrated in FIG. 1 and may be another appropriate position.
  • the sensor 5 illustrated in FIG. 1 may be installed on a left side, on a right side, and/or at a rear portion of the mobility device 100.
  • the number of such sensors 5 may be any number equal to or greater than 1 depending on various conditions (or requirements) such as a range and/or an accuracy of measurement performed at the mobility device 100.
  • the sensor 5 may be installed inside the mobility device 100.
  • the inside the mobility device 100 may be, for example, a space inside a bumper, a space inside a body, a space inside a headlight, or a space such as a driver's space.
  • the sensor 5 transmits an electromagnetic wave as a transmission wave from the transmission antenna. For example, when a predetermined object (for example, an object 200 illustrated in FIG. 1 ) is located around the mobility device 100, at least part of the transmission wave transmitted from the sensor 5 is reflected off the object to become a reflected wave. For example, the reception antenna of the sensor 5 receives such a reflected wave. In this manner, the electronic device 1 mounted in the mobility device 100 can detect the object as a target.
  • a predetermined object for example, an object 200 illustrated in FIG. 1
  • the sensor 5 including the transmission antenna may be typically a radar (Radio Detecting and Ranging) sensor that transmits and receives a radio wave.
  • the sensor 5 is not limited to a radar sensor.
  • the sensor 5 according to the one embodiment may be, for example, a sensor based on the LIDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging) technology that uses an optical wave.
  • LIDAR Light Detection and Ranging, Laser Imaging Detection and Ranging
  • Each of these sensors can include, for example, a patch antenna. Since the technologies such as the radar and the LIDAR are already known, detailed description may be appropriately simplified or omitted.
  • the electronic device 1 mounted in the mobility device 100 illustrated in FIG. 1 receives, from the reception antenna, the reflected wave of the transmission wave transmitted from the transmission antenna of the sensor 5. In this manner, the electronic device 1 can detect, as the target, the predetermined object 200 located within a predetermined distance from the mobility device 100. For example, as illustrated in FIG. 1 , the electronic device 1 can measure a distance A between the mobility device 100, which is a vehicle of interest, and the predetermined object 200. The electronic device 1 can also measure a relative velocity between the mobility device 100, which is the vehicle of interest, and the predetermined object 200. The electronic device 1 can further measure a direction (an angle of arrival ⁇ ) from which the reflected wave from the predetermined object 200 arrives at the mobility device 100, which is the vehicle of interest.
  • the object 200 may be, for example, at least any of an oncoming automobile traveling in a lane adjacent to a lane of the mobility device 100, an automobile traveling next to the mobility device 100, an automobile traveling in front of or behind the mobility device 100 in the same lane, or the like.
  • the object 200 may also be any object located around the mobility device 100, such as a motorcycle, a bicycle, a stroller, a person such as a pedestrian, an animal, other forms of life such as an insect, a guardrail, a median strip, a road sign, a step on a sidewalk, a wall, a maintenance hole, or an obstacle.
  • the object 200 may be in motion or stationary.
  • the object 200 may be an automobile or the like that is parked or stationary around the mobility device 100.
  • the object detected by the sensor 5 includes a living thing such as a person or an animal in addition to a non-living thing.
  • the object detected by the sensor 5 in the present disclosure includes a target, which includes a person, an object, and an animal, to be detected with the radar technology.
  • FIG. 1 a ratio between a size of the sensor 5 and a size of the mobility device 100 does not necessarily indicate an actual ratio.
  • FIG. 1 illustrates the sensor 5 that is installed at an outer portion of the mobility device 100. However, in one embodiment, the sensor 5 may be installed at various positions of the mobility device 100. For example, in one embodiment, the sensor 5 may be installed inside a bumper of the mobility device 100 so as not to be seen in the appearance of the mobility device 100.
  • the transmission antenna of the sensor 5 transmits a radio wave in a frequency band, such as a millimeter wave (equal to or higher than 30 GHz) or a quasi-millimeter wave (for example, around 20 GHz to 30 GHz) as a typical example.
  • the transmission antenna of the sensor 5 may transmit a radio wave having a frequency bandwidth of 4 GHz such as from 77 GHz to 81 GHz.
  • FIG. 2 is a functional block diagram schematically illustrating an example of a configuration of the electronic device 1 according to the one embodiment. An example of the configuration of the electronic device 1 according to the one embodiment is described below.
  • a frequency-modulated continuous wave radar (hereinafter, referred to as an FMCW radar) is often used.
  • the FMCW radar sweeps a frequency of a to-be-transmitted radio wave to generate a transmission signal.
  • a frequency of the radio wave used by such a millimeter-wave FMCW radar which uses a radio wave of a frequency band of 79 GHz, for example, has a frequency bandwidth of 4 GHz such as from 77 GHz to 81 GHz, for example.
  • the radar of the frequency band of 79 GHz has a feature that a usable frequency bandwidth is wider than other millimeter-wave and/or quasi-millimeter-wave radars of frequency bands of 24 GHz, 60 GHz, and 76 GHz, for example. Such an embodiment is described below as an example.
  • the electronic device 1 includes the sensor 5 and an ECU (Electronic Control Unit) 50.
  • the ECU 50 controls various operations of the mobility device 100.
  • the ECU 50 may include at least one or more ECUs.
  • the electronic device 1 according to the one embodiment includes the controller 10.
  • the electronic device 1 according to the one embodiment may also appropriately include another functional unit such as at least any of a transmission unit 20 or reception units 30A to 30D.
  • the electronic device 1 may include multiple reception units such as the reception units 30A to 30D. When the reception units 30A, 30B, 30C, and 30D are not distinguished from one another, the reception units 30A, 30B, 30C, and 30D are simply referred to as "reception units 30" below.
  • the controller 10 may include a distance FFT processing unit 11, a velocity FFT processing unit 12, a threshold determining unit 13, an angle-of-arrival estimating unit 14, an object detecting unit 15, a tracking processing unit 16, a storage unit 17, and a target classifying unit 18. These functional units included in the controller 10 are further described later.
  • the transmission unit 20 may include a signal generating unit 21, a synthesizer 22, phase control units 23A and 23B, amplifiers 24A and 24B, and transmission antennas 25A and 25B.
  • phase control units 23A and 23B are simply referred to as "phase control units 23" below.
  • amplifiers 24A and 24B are not distinguished from each other, the amplifiers 24A and 24B are simply referred to as "amplifiers 24" below.
  • transmission antennas 25A and 25B are simply referred to as "transmission antennas 25" below.
  • each of the reception units 30 may include a respective one of reception antennas 31A to 31D.
  • the reception antennas 31A, 31B, 31C, and 31D are simply referred to as "reception antennas 31" below.
  • each of the multiple reception units 30 may include an LNA 32, a mixer 33, an IF unit 34, and an AD conversion unit 35.
  • the reception units 30A to 30D may have the same and/or similar configuration.
  • FIG. 2 schematically illustrates the configuration of only the reception unit 30A as a representative example.
  • the sensor 5 described above may include, for example, the transmission antennas 25 and the reception antennas 31.
  • the sensor 5 may also appropriately include at least any of other functional units such as the controller 10.
  • the controller 10 included in the electronic device 1 is capable of controlling the individual functional units of the electronic device 1 and controlling operations of the entire electronic device 1.
  • the controller 10 may include at least one processor, for example, a CPU (Central Processing Unit) or a DSP (Digital Signal Processor).
  • the controller 10 may be collectively implemented by one processor, may be implemented by some processors, or may be implemented by discrete individual processors.
  • the processor may be implemented as one integrated circuit.
  • the integrated circuit is also referred to as an IC.
  • the processor may be implemented as multiple integrated circuits and discrete circuits connected to be able to perform communication.
  • the processor may be implemented based on various other known technologies.
  • the controller 10 may be configured as, for example, a CPU (hardware) and a program (software) executed by the CPU.
  • the controller 10 may appropriately include a memory necessary for operations of the controller 10.
  • the controller 10 is capable of controlling at least one of the transmission unit 20 or the reception units 30.
  • the controller 10 may control at least one of the transmission unit 20 or the reception units 30, based on various kinds of information stored in the any storage unit (memory).
  • the controller 10 may instruct the signal generating unit 21 to generate a signal or may control the signal generating unit 21 to generate a signal.
  • the signal generating unit 21 In accordance with control performed by the controller 10, the signal generating unit 21 generates a signal (transmission signal) to be transmitted as a transmission wave T from each of the transmission antennas 25.
  • the signal generating unit 21 may allocate a frequency of the transmission signal in accordance with control performed by the controller 10, for example. Specifically, the signal generating unit 21 may allocate the frequency of the transmission signal in accordance with a parameter set by the controller 10, for example.
  • the signal generating unit 21 receives frequency information from the controller 10 or the any storage unit (memory) and generates a signal having a predetermined frequency in a frequency band such as from 77 GHz to 81 GHz, for example.
  • the signal generating unit 21 may include a functional unit such as a voltage control oscillator (VCO), for example.
  • VCO voltage control oscillator
  • the signal generating unit 21 may be configured as hardware having the function, for example as a microcomputer, or for example as a processor such as a CPU and a program or the like executed by the processor.
  • Each functional unit described below may also be configured as hardware having the function, for example as a microcomputer if possible, or for example as a processor such as a CPU and a program or the like executed by the processor if possible.
  • the signal generating unit 21 may generate a transmission signal (transmission chirp signal) such as a chirp signal, for example.
  • the signal generating unit 21 may generate a signal (linear chirp signal) whose frequency changes linearly and periodically.
  • the signal generating unit 21 may generate a chirp signal whose frequency linearly and periodically increases from 77 GHz to 81 GHz as time elapses.
  • the signal generating unit 21 may generate a signal whose frequency periodically repeats a linear increase (up-chirp) from 77 GHz to 81 GHz and a decrease (down-chirp) as time elapses.
  • the controller 10 may set in advance the signal generated by the signal generating unit 21.
  • the any storage unit (memory) or the like may store in advance the signal generated by the signal generating unit 21. Since a chirp signal used in a technical field such as the radar is known, more detailed description is appropriately simplified or omitted.
  • the signal generated by the signal generating unit 21 is supplied to the synthesizer 22.
  • FIG. 4 is a diagram for describing an example of chirp signals generated by the signal generating unit 21.
  • the horizontal axis represents elapsed time and the vertical axis represents a frequency.
  • the signal generating unit 21 generates linear chirp signals whose frequency changes linearly and periodically.
  • FIG. 4 illustrates chirp signals c1, c2, ..., c8.
  • the frequency of each chirp signal linearly increases as time elapses.
  • one subframe includes eight chirp signals c1, c2, ..., c8. That is, each of subframes such as a subframe 1 and a subframe 2 illustrated in FIG. 4 includes eight chirp signals c1, c2, ..., c8.
  • one frame includes 16 subframes such as the subframes 1 to 16. That is, each of frames such as a frame 1 and a frame 2 illustrated in FIG. 4 includes 16 subframes.
  • a frame interval of a predetermined length may be included between frames.
  • One frame illustrated in FIG. 4 may have a length of about 30 ms to 50 ms, for example.
  • the frame 2 and subsequent frames may have the same and/or similar configuration.
  • the frame 3 and subsequent frames may have the same and/or similar configuration.
  • the signal generating unit 21 may generate a transmission signal as any number of frames.
  • an illustration of some chirp signals is omitted.
  • the any storage unit (memory) or the like may store a relationship between time and a frequency of the transmission signal generated by the signal generating unit 21.
  • the electronic device 1 may transmit a transmission signal made up of subframes each including multiple chirp signals.
  • the electronic device 1 according to the one embodiment may transmit a transmission signal made up of frames each including a predetermined number of subframes.
  • the electronic device 1 transmits a transmission signal having a frame structure illustrated in FIG. 4 .
  • the frame structure illustrated in FIG. 4 is an example.
  • the number of chirp signals included in one subframe is not limited to eight.
  • the signal generating unit 21 may generate a subframe including any number of (for example, multiple) chirp signals.
  • the subframe structure illustrated in FIG. 4 is also an example.
  • the number of subframes included in one frame is not limited to 16.
  • the signal generating unit 21 may generate a frame including any number of (for example, multiple) subframes.
  • the signal generating unit 21 may generate signals having different frequencies.
  • the signal generating unit 21 may generate multiple discrete signals of bandwidths in which frequencies f are different from each other.
  • the synthesizer 22 increases the frequency of the signal generated by the signal generating unit 21 to a frequency in a predetermined frequency band.
  • the synthesizer 22 may increase the frequency of the signal generated by the signal generating unit 21 to a frequency selected as a frequency of the transmission wave T to be transmitted from each of the transmission antennas 25.
  • the controller 10 may set the frequency selected as the frequency of the transmission wave T to be transmitted from each of the transmission antennas 25.
  • the any storage unit may store the frequency selected as the frequency of the transmission wave T to be transmitted from each of the transmission antennas 25.
  • the signal whose frequency has been increased by the synthesizer 22 is supplied to the phase control unit 23 and the mixer 33.
  • the signal whose frequency has been increased by the synthesizer 22 may be supplied to each of the multiple phase control units 23.
  • the signal whose frequency has been increased by the synthesizer 22 may be supplied to the mixer 33 of each of the multiple reception units 30.
  • Each of the phase control units 23 controls a phase of the transmission signal supplied from the synthesizer 22. Specifically, for example, in accordance with control performed by the controller 10, each of the phase control units 23 may appropriately advance or delay the phase of the signal supplied from the synthesizer 22 to adjust the phase of the transmission signal. In this case, based on a difference between paths of the transmission waves T to be transmitted from the multiple transmission antennas 25, the phase control units 23 may adjust the phases of the respective transmission signals. The phase control units 23 appropriately adjust the phases of the respective transmission signals, so that the transmission waves T transmitted from the multiple transmission antennas 25 enhance with each other in a predetermined direction to form a beam (beamforming).
  • the any storage unit may store a correlation between a direction of beamforming and amounts of phase by which the respective transmission signals transmitted by the multiple transmission antennas 25 are to be controlled.
  • the transmission signal whose phase is controlled by each of the phase control units 23 is supplied to a respective one of the amplifiers 24.
  • the amplifier 24 amplifies power (electric power) of the transmission signal supplied from the phase control unit 23 in accordance with control performed by the controller 10, for example.
  • each of the multiple amplifiers 24 may amplify power (electric power) of the transmission signal supplied from a respective one of the phase control units 23 in accordance with control performed by the controller 10, for example. Since the technology for amplifying power of a transmission signal is already known, more detailed description is omitted.
  • the amplifier 24 is connected to the transmission antenna 25.
  • the transmission antenna 25 outputs (transmits), as the transmission wave T, the transmission signal amplified by the amplifier 24.
  • each of the multiple transmission antennas 25 may output (transmit), as the transmission wave T, the transmission signal amplified by a respective one of the multiple amplifiers 24. Since the transmission antennas 25 can have a configuration that is the same as and/or similar to the configuration of transmission antennas for use in the known radar technology, more detailed description is omitted.
  • the electronic device 1 which includes the transmission antennas 25, can transmit transmission signals (for example, transmission chirp signals) as the transmission waves T from the respective transmission antennas 25.
  • transmission signals for example, transmission chirp signals
  • At least one of the functional units of the electronic device 1 may be housed in one housing.
  • the one housing may have a hard-to-open structure.
  • the transmission antennas 25, the reception antennas 31, and the amplifiers 24 are desirably housed in one housing, and this housing desirably has a hard-to-open structure.
  • each of the transmission antennas 25 may transmit the transmission wave T to outside the mobility device 100 through a cover member such as a radar cover, for example.
  • the radar cover may be made of a material, for example, a synthetic resin or rubber, that allows an electromagnetic wave to pass therethrough.
  • This radar cover may also serve as a housing of the sensor 5, for example. Covering the transmission antennas 25 with a member such as the radar cover can reduce a risk of the transmission antennas 25 being damaged or malfunctioning because of a contact with an external object.
  • the radar cover and the housing may also be referred to as a radome.
  • FIG. 2 illustrates an example of the electronic device 1 that includes two transmission antennas 25.
  • the electronic device 1 may include any number of transmission antennas 25.
  • the electronic device 1 may include the multiple transmission antennas 25 when the transmission waves T transmitted from the respective transmission antennas 25 form a beam in a predetermined direction.
  • the electronic device 1 may include multiple transmission antennas 25.
  • the electronic device 1 may include the multiple phase control units 23 and the multiple amplifiers 24 to correspond to the multiple transmission antennas 25.
  • Each of the multiple phase control units 23 may control the phase of a respective one of the multiple transmission waves supplied from the synthesizer 22 and to be transmitted from the respective transmission antennas 25.
  • Each of the multiple amplifiers 24 may amplify power of a respective one of the multiple transmission signals to be transmitted from the respective transmission antennas 25.
  • the sensor 5 may include the multiple transmission antennas.
  • the electronic device 1 illustrated FIG. 2 includes the multiple transmission antennas 25, the electronic device 1 may include multiple functional units necessary for transmitting the transmission waves T from the multiple transmission antennas 25.
  • the reception antenna 31 receives the reflected wave R.
  • the reflected wave R may be the transmission wave T reflected off the predetermined object 200.
  • the reception antenna 31 may include multiple antennas such as the reception antennas 31A to 31D, for example. Since the reception antennas 31 can have a configuration that is the same as and/or similar to the configuration of reception antennas for use in the known radar technology, more detailed description is omitted.
  • the reception antenna 31 is connected to the LNA 32. A reception signal based on the reflected wave R received by the reception antenna 31 is supplied to the LNA 32.
  • the electronic device 1 can receive, from each of the multiple reception antennas 31, the reflected wave R that is the transmission wave T that has been transmitted as the transmission signal (transmission chirp signal) such as a chirp signal, for example, and has been reflected off the predetermined object 200.
  • the transmission chirp signal is transmitted as the transmission wave T in this manner
  • the reception signal based on the received reflected wave R is referred to as a reception chirp signal. That is, the electronic device 1 receives the reception signal (for example, the reception chirp signal) as the reflected wave R from each of the reception antennas 31.
  • each of the reception antennas 31 may receive the reflected wave R from outside the mobility device 100 through a cover member such as a radar cover, for example.
  • the radar cover may be made of a material, for example, a synthetic resin or rubber, that allows an electromagnetic wave to pass therethrough.
  • This radar cover may also serve as a housing of the sensor 5, for example. Covering the reception antennas 31 with a member such as the radar cover can reduce a risk of the reception antennas 31 being damaged or malfunctioning because of a contact with an external object.
  • the radar cover and the housing may also be referred to as a radome.
  • one sensor 5 may include at least one transmission antenna 25 and at least one reception antenna 31.
  • one sensor 5 may include the multiple transmission antennas 25 and the multiple reception antennas 31.
  • one radar sensor may be covered with a cover member such as one radar cover, for example.
  • the LNA 32 amplifies, with low noise, the reception signal based on the reflected wave R received by the reception antenna 31.
  • the LNA 32 may be a low-noise amplifier and amplifies, with low noise, the reception signal supplied from the reception antenna 31.
  • the reception signal amplified by the LNA 32 is supplied to the mixer 33.
  • the mixer 33 mixes (multiplies) the reception signal having a radio frequency (RF) and supplied from the LNA 32 and the transmission signal supplied from the synthesizer 22 to generate a beat signal.
  • the beat signal obtained by the mixer 33 through mixing is supplied to the IF unit 34.
  • the IF unit 34 performs frequency conversion on the beat signal supplied from the mixer 33 to decrease the frequency of the beat signal to an intermediate frequency (IF).
  • IF intermediate frequency
  • the beat signal whose frequency has been decreased by the IF unit 34 is supplied to the AD conversion unit 35.
  • the AD conversion unit 35 digitizes the analog beat signal supplied from the IF unit 34.
  • the AD conversion unit 35 may be configured as any analog-to-digital conversion circuit (Analog-to-Digital Converter (ADC)).
  • ADC Analog-to-Digital Converter
  • the digitized beat signal obtained by the AD conversion unit 35 is supplied to the distance FFT processing unit 11 of the controller 10.
  • the digitized beat signals obtained by the respective AD conversion units 35 may be supplied to the distance FFT processing unit 11 of the controller 10.
  • the distance FFT processing unit 11 of the controller 10 estimates a distance between the mobility device 100 equipped with the electronic device 1 and the object 200, based on the beat signals supplied from the respective AD conversion units 35.
  • the distance FFT processing unit 11 may include a processing unit that performs fast Fourier transform, for example.
  • the distance FFT processing unit 11 may be configured as any circuit, any chip, or the like that performs fast Fourier transform (FFT).
  • the distance FFT processing unit 11 performs FFT processing (hereinafter, appropriately referred to as "distance FFT processing") on the digitized beat signals obtained by the AD conversion units 35.
  • the distance FFT processing unit 11 may perform FFT processing on complex signals supplied from the AD conversion units 35.
  • the digitized beat signals obtained by the AD conversion units 35 can be represented as temporal changes in signal intensity (power).
  • the distance FFT processing unit 11 performs FFT processing on such a beat signal, so that the beat signal can be represented as a signal intensity (power) for each frequency. If a peak in a result obtained by the distance FFT processing is equal to or greater than a predetermined threshold, the distance FFT processing unit 11 may determine that the predetermined object 200 is located at the distance corresponding to the peak.
  • an object that reflects a transmission wave is determined to be present if a peak value that is equal to or greater than a threshold is detected from the average power or amplitude of a disturbance signal.
  • the threshold determining unit 13 may determine whether an object is present based on such a threshold.
  • the electronic device 1 can detect, as the target, the object 200 that reflects the transmission wave T, based on the transmission signal transmitted as the transmission wave T and the reception signal received as the reflected wave R.
  • the distance FFT processing unit 11 can estimate a distance to the predetermined object, based on one chirp signal (for example, c1 illustrated in FIG. 4 ). That is, the electronic device 1 can measure (estimate) the distance A illustrated in FIG. 1 by performing the distance FFT processing. Since a technique for measuring (estimating) a distance to a predetermined object by performing FFT processing on a beat signal is known, more detailed description is appropriately simplified or omitted.
  • the result (for example, distance information) of the distance FFT processing performed by the distance FFT processing unit 11 may be supplied to the velocity FFT processing unit 12.
  • the result of the distance FFT processing performed by the distance FFT processing unit 11 may also be supplied to another functional unit such as the threshold determining unit 13, for example.
  • the velocity FFT processing unit 12 estimates a relative velocity between the mobility device 100 equipped with the electronic device 1 and the object 200, based on the beat signals on which the distance FFT processing has been performed by the distance FFT processing unit 11.
  • the velocity FFT processing unit 12 may include a processing unit that performs fast Fourier transform, for example.
  • the velocity FFT processing unit 12 may be configured as any circuit, any chip, or the like that performs fast Fourier transform (FFT).
  • the velocity FFT processing unit 12 further performs FFT processing (hereinafter, appropriately referred to as "velocity FFT processing") on the beat signals on which the distance FFT processing unit 11 has performed the distance FFT processing.
  • the velocity FFT processing unit 12 may perform FFT processing on the complex signals supplied from the distance FFT processing unit 11.
  • the velocity FFT processing unit 12 can estimate a relative velocity of the predetermined object, based on a subframe (for example, the subframe 1 illustrated in FIG. 4 ) including chirp signals. Through the distance FFT processing performed on the beat signals in the above-described manner, multiple vectors can be generated.
  • the velocity FFT processing unit 12 can estimate a relative velocity to the predetermined object by determining a phase of a peak in a result of the velocity FFT processing performed on these multiple vectors. That is, the electronic device 1 can measure (estimate) a relative velocity between the mobility device 100 and the predetermined object 200 illustrated in FIG. 1 by performing the velocity FFT processing. Since a technique for measuring (estimating) a relative velocity of a predetermined object by performing velocity FFT processing on a result of distance FFT processing is known, more detailed description is appropriately simplified or omitted.
  • the result (for example, velocity information) of the velocity FFT processing performed by the velocity FFT processing unit 12 may be supplied to the threshold determining unit 13.
  • the result of the velocity FFT processing performed by the velocity FFT processing unit 12 may also be supplied to another functional unit such as the angle-of-arrival estimating unit 14, for example.
  • the threshold determining unit 13 performs determination processing for a distance and/or a relative velocity, based on the result of the distance FFT processing performed by the distance FFT processing unit 11 and/or the result of the velocity FFT processing performed by the velocity FFT processing unit 12.
  • the threshold determining unit 13 may perform the determination based on a predetermined threshold. For example, the threshold determining unit 13 may determine whether the result of the distance FFT processing performed by the distance FFT processing unit 11 and/or the result of the velocity FFT processing performed by the velocity FFT processing unit 12 exceeds a predetermined threshold.
  • the threshold determining unit 13 may determine that an object has been detected at the distance and/or the relative velocity at which the result exceeds the predetermined threshold.
  • the threshold determining unit 13 may output results exceeding the predetermined threshold among the results of the distance FFT processing performed by the distance FFT processing unit 11 and/or the results of the velocity FFT processing performed by the velocity FFT processing unit 12.
  • the operation performed by the threshold determining unit 13 may be same as and/or similar to, for example, detection processing based on a constant false alarm rate (CFAR).
  • the operation performed by the threshold determining unit 13 may be processing based on Order Statistic CFAR (OS-CFAR).
  • OS-CFAR Order Statistic CFAR
  • OS-CFER is a technique in which a threshold is set based on ordered statistics and a target is determined to be present if the signal intensity exceeds the threshold.
  • the result of the threshold-based determination processing performed by the threshold determining unit 13 may be supplied to the angle-of-arrival estimating unit 14.
  • the result of the processing performed by the threshold determining unit 13 may be supplied to another functional unit such as the object detecting unit 15, for example.
  • the angle-of-arrival estimating unit 14 may estimate the direction from which the reflected wave R arrives from the predetermined object 200, based on the result of the velocity FFT processing performed by the velocity FFT processing unit 12 and/or the output from the threshold determining unit 13.
  • the angle-of-arrival estimating unit 14 may estimate the direction from which the reflected wave R arrives from the predetermined object 200, based on the result output from the threshold determining unit 13 among the results of the velocity FFT processing performed by the velocity FFT processing unit 12.
  • the electronic device 1 can estimate the direction from which the reflected wave R arrives, by receiving the reflected wave R from the multiple reception antennas 31.
  • the multiple reception antennas 31 are arranged at a predetermined interval.
  • the transmission wave T transmitted from each of the transmission antennas 25 is reflected off the predetermined object 200 to become the reflected wave R.
  • Each of the multiple reception antennas 31 arranged at the predetermined interval receives the reflected wave R.
  • the angle-of-arrival estimating unit 14 can estimate the direction from which the reflected wave R arrives at each of the multiple reception antennas 31, based on the phase of the reflected wave R received by the reception antenna 31 and a difference in path of the reflected wave R. That is, the electronic device 1 can measure (estimate) the angle of arrival ⁇ illustrated in FIG. 1 , based on the result of the velocity FFT processing.
  • the angle-of-arrival estimating unit 14 may estimate a direction from which the reflected wave arrives, based on complex signals received by the multiple reception antennas 31 at the velocity at which the object is determined to be present. As described above, the electronic device 1 according to the one embodiment can estimate an angle of the direction in which the object is present.
  • MUSIC Multiple Signal Classification
  • ESPRIT Estimat of Signal Parameters via Rotational Invariance Technique
  • Information (angle information) on the angle of arrival ⁇ estimated by the angle-of-arrival estimating unit 14 may be supplied to the object detecting unit 15.
  • the object detecting unit 15 determines whether an object is detected as the target (for example, by clustering), based on information on the direction (angle) from which the reflected wave arrives, information on the relative velocity to the target, and/or information on the distance to the target.
  • the information on the direction (angle) from which the reflected wave arrives may be acquired from the angle-of-arrival estimating unit 14.
  • the information on the relative velocity and the distance to the target may be acquired from the threshold determining unit 13.
  • the information on the relative velocity to the target may be acquired from the velocity FFT processing unit 12.
  • the information on the distance to the target may be acquired from the distance FFT processing unit 11.
  • the object detecting unit 15 may calculate average power at points constituting the object detected as the target.
  • the object detecting unit 15 detects an object located in a range to which the transmission wave T is transmitted, based on the information supplied from at least any of the distance FFT processing unit 11, the velocity FFT processing unit 12, the threshold determining unit 13, or the angle-of-arrival estimating unit 14.
  • the object detecting unit 15 may perform detection of an object by performing, for example, clustering processing based on the supplied distance information, velocity information, and angle information.
  • clustering processing for example, average power of points constituting the detected object may be calculated.
  • the distance information, the velocity information, the angle information, and power information of the object detected by the object detecting unit 15 may be supplied to the tracking processing unit 16.
  • the output from the object detecting unit 15 may be supplied to another functional unit such as the ECU 50, for example.
  • the mobility device 100 is an automobile, communication may be performed using a communication interface such as a CAN (Controller Area Network), for example.
  • CAN Controller Area Network
  • the tracking processing unit 16 performs processing of predicting a target position, in the next frame, of the object subjected to the clustering processing performed by the object detecting unit 15.
  • the tracking processing unit 16 may predict the position of the object, in the next frame, subjected to the clustering processing, by using a Kalman filter, for example.
  • the tracking processing unit 16 may store the predicted position of the object in the next frame in the storage unit 17, for example.
  • the storage unit 17 can be implemented by, but not limited to, a semiconductor memory or a magnetic disk, for example, and may be implemented by any storage device.
  • the storage unit 17 may be, for example, a storage medium such as a memory card inserted to the electronic device 1 according to the present embodiment.
  • the storage unit 17 may be an internal memory of the CPU used as the controller 10 as described above.
  • the storage unit 17 may store a program executed by the controller 10, results of processing performed by the controller 10, and so on.
  • the storage unit 17 may function as a work memory of the controller 10.
  • the storage unit 17 may be the any storage unit (memory) described above.
  • the storage unit 17 may store various parameters for setting a range in which an object is detected based on the transmission wave T transmitted from each transmission antenna 25 and the reflected wave R received from each reception antenna 31.
  • the tracking processing unit 16 may perform data association between a position predicted in the previous frame and a clustering position detected in the frame of interest. For example, the tracking processing unit 16 may provide a restriction on a minimum Euclidean distance, a minimum Mahalanobis distance, or a velocity. The tracking processing unit 16 may perform association between time frames in this manner.
  • the tracking processing unit 16 may accumulate velocity information of a point cloud representing the same target in the storage unit 17, for example. Once the velocity information indicating the point cloud representing the same target is accumulated for a required number of point clouds and a required number of frames, the tracking processing unit 16 calculates a probability density distribution of the velocity.
  • the storage unit 17 may store in advance a probability density distribution for reference (reference probability density distribution) of each target in advance.
  • the probability density distribution for reference of the target stored in a memory such as the storage unit 17, for example is also referred to as a "reference probability density distribution" as appropriate.
  • the target classifying unit 18 classifies whether the object is a predetermined target, based on the information on the detected object. To this end, the target classifying unit 18 may calculate a probability density distribution, based on a velocity satisfying the required number of point clouds in the frame and the required number of frames. The target classifying unit 18 may classify the target, based on the reference probability density distribution stored in a memory such as the storage unit 17, for example, and the probability density distribution calculated from the velocity satisfying the required number of point clouds in the frame and the required number of frames. The target classifying unit 18 may calculate a Kullback-Leibler divergence from the calculated probability density distribution and each of the reference probability density distributions stored in the memory.
  • the target classifying unit 18 may classify, as the predetermined target, a target for which the calculated Kullback-Leibler divergence is equal to or less than a predetermined threshold and has a smallest numerical value.
  • the Kullback-Leibler divergence is also referred to as a "KL divergence" as appropriate.
  • the target classifying unit 18 may output a target classifying result (detection result) obtained in this manner to the ECU 50, for example.
  • the target classifying unit 18 may successively perform updating in subsequent frames satisfying the required number of point clouds and the required number of frames, and calculate the probability density distribution. For example, in the memory such as the storage unit 17, information on the old point clouds may be deleted.
  • the ECU 50 included in the electronic device 1 is capable of controlling functional units of the mobility device 100 and controlling operations of the entire mobility device 100.
  • the ECU 50 may include at least one processor, for example, a CPU (Central Processing Unit) or a DSP (Digital Signal Processor).
  • the ECU 50 may be collectively implemented by one processor, may be implemented by some processors, or may be implemented by discrete individual processors.
  • the processor may be implemented as one integrated circuit.
  • the integrated circuit is also referred to as an IC.
  • the processor may be implemented as multiple integrated circuits and discrete circuits connected to be able to perform communication.
  • the processor may be implemented based on various other known technologies.
  • the ECU 50 may be configured as, for example, a CPU and a program executed by the CPU.
  • the ECU 50 may appropriately include a memory necessary for operations of the ECU 50.
  • At least part of the functions of the controller 10 may be functions of the ECU 50, or at least part of the functions of the ECU 50 may be functions of the controller 10.
  • the electronic device 1 illustrated in FIG. 2 includes the two transmission antennas 25 and the four reception antennas 31.
  • the electronic device 1 according to the one embodiment may include any number of transmission antennas 25 and any number of reception antennas 31.
  • the electronic device 1 since the electronic device 1 includes the two transmission antennas 25 and the four reception antennas 31, the electronic device 1 can be considered to include a virtual antenna array virtually including eight antennas.
  • the electronic device 1 may receive the reflected wave R of 16 subframes illustrated in FIG. 4 by using, for example, the eight virtual antennas.
  • Target classifying processing performed by the electronic device 1 according to the one embodiment is described.
  • the electronic device 1 transmits a transmission wave from the transmission antenna and receives, from the reception antenna, a reflected wave that is the transmission wave reflected off an object.
  • the electronic device 1 according to the one embodiment may detect the object that reflects the transmission wave, based on the transmission signal and/or the reception signal.
  • the electronic device 1 according to the one embodiment classifies whether the object detected in this manner is a predetermined target.
  • the electronic device 1 according to the one embodiment classifies the object detected in the above-described manner as a target among the predetermined target candidates. An algorithm of such processing is further described below.
  • the electronic device 1 performs the target classifying processing, based on a Doppler velocity observed by the radar.
  • the Doppler velocity observed by the radar of the electronic device 1 may be, for example, a relative velocity of an object detected by the electronic device 1 relative to the electronic device 1.
  • one Doppler velocity is observed for each object in one frame such as the frame 1 illustrated in FIG. 4 , for example.
  • the electronic device 1 may continuously acquire and analyze such a Doppler velocity over a predetermined time or longer.
  • the electronic device 1 performs the target classifying processing based on such analysis.
  • the target to be classified by the electronic device 1 may be categorized into a class and a subclass.
  • the class of the target may indicate the type of the target.
  • the class of the target may indicate the type of the target such as whether the target is an automobile, a two-wheeled vehicle, a bicycle, or a pedestrian.
  • the subclass of the target may be a subcategory to which the target is classified in the class of the target and/or a subcategory to which the target is categorized in accordance with a motion state of the target.
  • the subclass of the target may be a subcategory of a pedestrian categorized in accordance with whether the pedestrian is an adult pedestrian, a child pedestrian, or an elderly pedestrian.
  • the subclass of the target may be a subcategory such as a slowly walking pedestrian or a fast walking pedestrian to which the target is classified by the motion state of the pedestrian.
  • the electronic device 1 may calculate a probability density distribution (probability density function (PDF)) from the Doppler velocity continuously acquired in the above-described manner.
  • PDF probability density function
  • the electronic device 1 may organize a list V r of velocity distributions acquired for an l-th (lowercase letter of the alphabet L) target into a frequency distribution table, perform normalization to make the total frequency equal to 1, and use this result as a probability density distribution p t l .
  • the probability density distribution thus obtained is also referred to as "probability density distribution based on observation” as appropriate.
  • the electronic device 1 may calculate a reference probability density distribution p r i,k in advance and store the reference probability density distribution p r i,k in any memory such as the storage unit 17, for example.
  • the reference probability density distribution may be stored in any location such as the electronic device 1, an external processor, or an external storage.
  • FIG. 5 is a diagram illustrating an example of a reference probability density distribution for pedestrians.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the electronic device 1 may calculate a distance between the probability density distribution p t l and the reference probability density distribution p r i,k (a difference between probability distributions).
  • the distance between the probability density distributions may be calculated using a KL divergence D KL [k, i, l], for example.
  • the distance between the probability density distributions may be calculated using a Pearson divergence, a relative Pearson divergence, or an L 2 distance, for example.
  • FIG. 6 is a diagram illustrating an example of a probability density distribution based on observation of a pedestrian.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the KL divergence D KL between the probability density distribution based on observation of a pedestrian illustrated in FIG. 6 and the reference probability density distribution for pedestrians illustrated in FIG. 5 is calculated to be 0.18.
  • FIG. 7 is a diagram illustrating an example of a probability density distribution based on observation of a bicycle.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the KL divergence D KL between the probability density distribution based on observation of a bicycle illustrated in FIG. 7 and the reference probability density distribution for pedestrians illustrated in FIG. 5 is calculated to be 0.82.
  • FIG. 8 is a diagram illustrating an example of a probability density distribution based on observation of an automobile.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the KL divergence D KL between the probability density distribution based on observation of an automobile illustrated in FIG. 8 and the reference probability density distribution for pedestrians illustrated in FIG. 5 is calculated to be 2.24.
  • the electronic device 1 calculates the distances between the probability density distributions (the differences between the probability distributions) using, for example, the KL divergences D KL [k, i, l], the electronic device 1 compares the calculation results with a threshold D KL,Th . As a result of this comparison, the electronic device 1 according to the one embodiment may output a class and a subclass for which the distance between the probability density distributions (the difference between the probability distributions) satisfying a condition of the threshold D KL,Th is the smallest.
  • the electronic device 1 may consecutively evaluate the continuously acquired Doppler velocities of each object for a predetermined time, i.e., T seconds (for example, from about 1 second to about 5 seconds) to classify the target based on characteristics of the probability density distribution of the velocities.
  • the electronic device 1 according to the one embodiment compares each object with the reference probability density distribution corresponding to each of the classes to one of which the target is desirably categorized.
  • the electronic device 1 assigns, to the target, the class and the subclass of the reference probability density distribution for which the KL divergence D KL is equal to or less than the predetermined threshold D KL,Th (for example, from about 0.1 to about 0.5) and for which the KL divergence is closest.
  • step 1 An algorithm of the target classifying processing performed by the electronic device 1 according to the one embodiment is further described.
  • the algorithm of the target classifying processing performed by the electronic device 1 described below may be roughly performed in two steps, namely, step 1 and step 2. Each step is described below.
  • the electronic device 1 may perform a process of acquiring (reading) the reference probability density distributions.
  • the electronic device 1 may choose all the reference probability density distributions p r i,k corresponding to the probability density distribution p t l based on observation of the l-th (lowercase letter of the alphabet L) target.
  • the electronic device 1 may calculate distances each between the probability density distribution p t l based on observation of the target and a respective one of the reference probability density distributions p r i,k (differences between the probability distributions).
  • the reference probability density distribution p r i,k has two indices (superscripts) for the class k and the subclass i. For example, when the distance between the probability density distributions (the difference between the probability distributions) satisfies the predetermined condition, the electronic device 1 stores the indices k, i, and D KL [k, i, l] in the any memory such as the storage unit 17.
  • the "predetermined condition" mentioned above may be, for example, that the KL divergence D KL is equal to or less than the predetermined threshold D KL,Th .
  • the indices k, i, and D KL [k, i, l] may be stored in a candidate list (see FIG. 11 ) of the object class stored in the any memory such as the storage unit 17.
  • the candidate list of the object class is further described below.
  • the KL divergence D KL may be calculated based on Expression (1) below, for example.
  • step 1 if a value i that is equal to or less than I and makes the KL divergence D KL [k, i, l] be equal to or less than the threshold D KL,Th is present, the electronic device 1 may store the indices k, i, and D KL [k, i, l] in the candidate list of the object class.
  • a condition that the value i that is equal to or less than I and makes the KL divergence D KL [k, i, l] be equal to or less than the threshold D KL,Th is present is referred to as a "first condition of class categorization" as appropriate.
  • step 1 the electronic device 1 calculates the KL divergence for the I reference probability density distributions of the k-th class. If the reference probability density distribution that makes the KL divergence be equal to or less than the predetermined threshold is present, the electronic device 1 stores the corresponding indices k, i, and D KL [k, i, l] in the candidate list of the object class.
  • step 1 if no value i that makes the KL divergence be equal to or less than the predetermined threshold is present, that is, if the candidate list of the object class is an empty set, this target is not categorized into any object.
  • the electronic device 1 may display an indication indicating that the target is not categorized into any object on any display or the like, for example.
  • the electronic device 1 may indicate that the target is not categorized into any object by outputting an indication such as "no relevant object class" or "others" on the any display or the like.
  • the electronic device 1 may select a set closest to the probability density distribution based on observation of the target from among the sets of the indices k, i, and D KL [k, i, l] recorded in the candidate list of the object class.
  • the electronic device 1 may select a set that satisfies a condition that a value k that is equal to or less than K and satisfies Expression (2) below is present.
  • the condition that the value k that is equal to or less than K and satisfies Expression (2) is present is also referred to as a "second condition of class categorization" as appropriate.
  • ⁇ represents a set of k and i satisfying the first condition of class categorization described above.
  • step 2 the electronic device 1 may assign the class and subclass selected in the above-described manner to the target.
  • step 2 the electronic device 1 selects a candidate having the smallest KL divergence for the probability density distribution p t j based on observation from the candidate list of the object class.
  • FIG. 9 is a diagram illustrating an example of the reference probability density distributions of the k-th class.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the superscript i indicates a subclass (subcategory/motion state of the target) in the k-th class (type of the target).
  • the example illustrated in FIG. 9 indicates the cases where i is from 1 to I.
  • FIG. 10 is a diagram illustrating an example of a probability density distribution based on observation of each target.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • An upper graph illustrated in FIG. 10 indicates an example of a probability density distribution p t 1 based on observation of a target 1.
  • a lower graph illustrated in FIG. 10 indicates an example of a probability density distribution p t J based on observation of a target 2.
  • the electronic device 1 calculates the KL divergences D KL [i, k, j] from the probability density distribution based on observation of the target 1 illustrated in the upper part of FIG. 10 and the respective reference probability density distributions illustrated in FIG. 9 .
  • the electronic device 1 may classify the target by comparing the calculated KL divergences D KL [i, k, j] with a predetermined threshold.
  • the electronic device 1 according to the one embodiment calculates the KL divergences D KL [i, k, j] from the probability density distribution based on observation of the target 2 illustrated in the lower part of FIG. 10 and the respective reference probability density distributions illustrated in FIG. 9 .
  • the electronic device 1 may classify the target by comparing the calculated KL divergences D KL [i, k, j] with a predetermined threshold.
  • FIG. 11 is a diagram illustrating an example of the candidate list of the object class.
  • FIG. 11 is a diagram illustrating an example of the candidate list of the object class stored in the any memory such as the storage unit 17.
  • FIG. 11 illustrates a candidate list of the object class for a j-th target.
  • the candidate list of the object class may be a list of an object class, a subclass, and a KL divergence.
  • the candidate list of the object class may be a list of the object class, the subclass, and the KL divergence that satisfy the "first condition of class categorization" described above, i.e., that are elements of the set ⁇ .
  • the electronic device 1 may store, in the any memory such as the storage unit 17, a set that satisfies the "first condition of class categorization” described above and is recognized as elements of the set ⁇ among the sets of the indexes k, i, and D KL [k, i, l].
  • the processing related to the "second condition of class categorization" described above is performed based on the KL divergences stored in the candidate list of the object class illustrated in FIG. 11 .
  • FIGs. 12 and 13 are diagrams for describing an algorithm of calculating a reference probability density distribution stored in advance in the any memory such as the storage unit 17.
  • the reference probability density distribution of each class may be created based on an algorithm below, for example.
  • the electronic device 1 may prepare probability density distributions q r l,i,k based on L pieces of observation data. In this case, the electronic device 1 may calculate the probability density distribution p r i,k such that the total sum of the KL divergences from these probability density distributions q r l,i,k is the smallest.
  • FIG. 12 is a diagram illustrating an example of the probability density distributions q r l,i,k .
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • the horizontal axis represents a velocity
  • the vertical axis represents a probability.
  • a procedure of the target classifying processing performed by the electronic device 1 according to the one embodiment is described.
  • FIGs. 14 and 15 are flowcharts illustrating an example of a procedure in which the electronic device performs the algorithm of the target classifying processing described above.
  • FIGs. 14 and 15 illustrate a process performed at time t by the electronic device 1 according to the one embodiment.
  • the electronic device 1 according to the one embodiment may perform the target classifying processing together with target tracking processing. That is, the target classifying processing performed by the electronic device 1 according to the one embodiment may be a combination of the processes illustrated in FIGs. 14 and 15 .
  • the process illustrated in FIG. 14 is related to tracking of a target.
  • the process illustrated in FIG. 14 may be performed by data association and Bayesian inference using a Kalman filter or the like.
  • the controller 10 loads an observed value of an object (cluster) (step S11).
  • the controller 10 can acquire the position of the target and the velocity (relative velocity) of the target calculated from the position.
  • the controller 10 performs data association between a posteriori estimated value at previous time (time t-1) and the observed value (step S12).
  • a posteriori estimated value at previous time time t-1
  • the observed value time t-1
  • an observed value, acquired at time t, of the position of the object and the velocity calculated from the position may be compared with the posteriori estimated value calculated with a Bayesian inference processing method using a Kalman filter or the like at the previous time t-1.
  • the controller 10 performs tracking processing using a Kalman filter, for example (step S13).
  • step S13 the controller 10 may perform processing of calculating the predicted value (priori estimated value) and processing of calculating the posteriori estimated value.
  • the controller 10 may derive the predicted value (priori estimated value) at the current time t from the posteriori estimated value at the previous time t-1.
  • the controller 10 may calculate the posteriori estimated value by Bayesian inference with the observed value, acquired at the current time t, subjected to data association with the predicted value (priori estimated value) at the current time t.
  • the Doppler velocity obtained as the observed value by the radar is a Doppler velocity in a normal direction of the reception antenna 31. That is, the electronic device 1 is unable to observe the velocity in the direction parallel to the reception antenna 31 in principle. Therefore, the Doppler velocity obtained as the observed value by the radar is different from the velocity calculated based on the position.
  • the velocity in the normal direction of the radar can be calculated based on the velocity calculated from the position.
  • the velocity in the normal direction of the radar which is calculated based on the velocity calculated from the position, tends to include many observation errors and the like.
  • the velocity in the normal direction of the radar thus calculated may be different from the Doppler velocity because of the influence of the observation errors or the like.
  • the electronic device 1 according to the one embodiment may use a Doppler velocity with an increased accuracy.
  • the electronic device 1 according to the one embodiment may use the velocity calculated from the position and having an accuracy increased by various kinds of processing.
  • the process illustrated in FIG. 15 is a flowchart for describing the target classifying processing performed by the electronic device 1 according to the one embodiment.
  • the target classifying processing performed by the electronic device 1 may include double-looped processing for the class k and the subclass i.
  • step S21 the controller 10 loads an observed value of an object (cluster) (step S21).
  • the processing of step S21 may be performed in the same or similar manner as or to the processing of step S11 described above.
  • step S21 the controller 10 can acquire information on the Doppler velocity of the target.
  • the controller 10 writes the Doppler velocity in a list vector V r in which Doppler velocities are listed (step S22).
  • the controller 10 calculates the probability density distribution p t j of the Doppler velocity (step S23).
  • the controller 10 reads out the reference probability density distributions p r i,k of the k-th class from the any memory such as the storage unit 17 (step S24). In step S24, the controller 10 may read out the reference probability density distributions p r i,k of the k-th class.
  • the controller 10 determines whether the probability density distribution p 0 of the object and the reference probability density distribution p r i satisfy a predetermined condition (step S25).
  • the predetermined condition in step S25 may be the "first condition of class categorization" described above.
  • step s25 the controller 10 may skip processing of step S26.
  • the controller 10 determines the number of loops (step S27). In step S27, the controller 10 may determine whether i is greater than I. If i is not greater than I in step S27, the controller 10 may add 1 to i (step S28), and the process may return to step S25. On the other hand, if i is greater than I in step S27, the controller 10 performs processing of step S29.
  • step S29 the controller 10 determines the number of loops (step S29). In step S29, the controller 10 may determine whether j is greater than J. If j is not greater than J in step S29, the controller 10 may add 1 to j (step S30) and the process may return to step S24. On the other hand, if j is greater than J in step S29, the controller 10 performs processing of step S31.
  • step S31 the controller 10 may set a class with the smallest KL divergence as the class of the object, and end the process illustrated in FIG. 15 .
  • the controller 10 may find the smallest KL divergence from among the KL divergences D KL,i , and set the corresponding class as the class of the object. In this case, the controller 10 may select one that satisfies the "second condition of class categorization" described above.
  • the controller 10 may classify a predetermined target, based on a probability density distribution calculated from a relative velocity of an object relative to the electronic device 1.
  • the controller 10 may determine whether the object is the predetermined target, based on the probability density distribution calculated from the relative velocity of the object relative to the electronic device 1.
  • the controller 10 may determine whether the object is the predetermined target, through comparison of the probability density distribution calculated from the relative velocity of the object relative to the electronic device 1 with the reference probability density distribution stored in advance in the storage unit 17.
  • the controller 10 may determine whether the object is the predetermined target, through comparison of distances between the probability density distribution calculated from the relative velocity of the object relative to the electronic device 1 and the reference probability density distributions.
  • the controller 10 may determine that the object is the predetermined target when a Kullback-Leibler divergence between the probability density distribution calculated from the relative velocity of the object relative to the electronic device 1 and the reference probability density distribution is equal to or less than a predetermined threshold.
  • the controller 10 may determine that the object is the predetermined target when a numerical value of the Kullback-Leibler divergence between the probability density distribution calculated from the relative velocity of the object relative to the electronic device 1 and the reference probability density distribution is smallest.
  • the controller 10 may classify the predetermined target, based on the probability density distribution calculated from a Doppler velocity of the object.
  • the electronic device 1 can calculate the probability density distribution of the velocity information of the target, and thus classify the target with a small number of patterns of the reference data of the target.
  • the electronic device 1 according to the one embodiment can reduce the processing load and/or the necessary memory.
  • the electronic device 1 according to the one embodiment can classify the target with a high accuracy.
  • each functional unit, each means, each step, or the like can be added to another embodiment or replaced with each functional unit, each means, each step, or the like in another embodiment without causing any logical contradiction.
  • multiple functional units, means, steps, or the like may be combined into one or may be divided.
  • the embodiments of the present disclosure described above are not limited to strict implementation according to the respective embodiments described above, and may be implemented by appropriately combining the features or omitting part thereof.
  • detection of an object may be performed in the determined object detection ranges by using the multiple sensors 5.
  • beamforming may be performed toward the determined object detection ranges by using the multiple sensors 5.
  • the embodiments described above are not limited to implementation as the electronic device 1.
  • the embodiments described above may be implemented as a method for controlling a device such as the electronic device 1.
  • the embodiments described above may be implemented as a program executed by a device such as the electronic device 1, a computer, or the like.
  • the electronic device 1 may include, as the minimum configuration, at least part of at least one of the sensor 5 or the controller 10, for example.
  • the electronic device 1 according to one embodiment may appropriately include at least any of the signal generating unit 21, the synthesizer 22, the phase control units 23, the amplifiers 24, or the transmission antennas 25 illustrated in FIG. 2 in addition to the controller 10.
  • the electronic device 1 according to the one embodiment may appropriately include at least any of the reception antenna 31, the LNA 32, the mixer 33, the IF unit 34, or the AD conversion unit 35 instead of or along with the functional units described above.
  • the electronic device 1 according to the one embodiment may include any storage unit (memory). As described above, the electronic device 1 according to the one embodiment can employ various configurations.
  • the electronic device 1 When the electronic device 1 according to the one embodiment is mounted in the mobility device 100, for example, at least any of the functional units described above may be installed at an appropriate place such as the inside of the mobility device 100. On the other hand, in one embodiment, for example, at least any of the transmission antennas 25 and the reception antennas 31 may be installed outside the mobility device 100.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Radar Systems Or Details Thereof (AREA)
EP21897741.1A 2020-11-27 2021-11-11 Dispositif électronique, procédé de commande de dispositif électronique et programme Pending EP4254005A1 (fr)

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PCT/JP2021/041634 WO2022113767A1 (fr) 2020-11-27 2021-11-11 Dispositif électronique, procédé de commande de dispositif électronique et programme

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